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rusted_core

A simple rust base to compute observables and correlations in point patterns and particle ensembles, in 2d and 3d

https://github.com/martiniani-lab/rusted_core

Science Score: 44.0%

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Keywords

correlations geometry observables physics
Last synced: 6 months ago · JSON representation ·

Repository

A simple rust base to compute observables and correlations in point patterns and particle ensembles, in 2d and 3d

Basic Info
  • Host: GitHub
  • Owner: martiniani-lab
  • Language: Rust
  • Default Branch: master
  • Homepage:
  • Size: 77.1 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
correlations geometry observables physics
Created over 2 years ago · Last pushed 11 months ago
Metadata Files
Readme Citation

README.md

Rusted Core

A simple code to compute usual correlations and observables in point patterns

Requires:

  • rust https://www.rust-lang.org/tools/install
  • maturin https://www.maturin.rs/installation
  • numpy
  • matplotlib
  • cmasher
  • hickle

Installation:

  1. Install rust, python, then pip install the python packages.
  2. From the main directory, run maturin develop --release
  3. Look at the example .py files, tweak the (for now) hard-coded values to take care of the relevant computation, then run it like a usual python script (This does not apply trivially to Apple Silicon for now -- maturin compiles but paths are messed up)
  4. Voilà!

Current functionalities

This is very much a WIP but the code already supports - Radial g(r) and radial field correlations (for arbitrary scalar or vector fields) in 2d and 3d, either connected or non-connected, for either square periodic or free boundary conditions. - Vector g(r) in 2d and 3d, with options to compute only up to a radial bound or to the p-th nearest metric neighbor - Radial or vector statistics of the p-th nearest metric neighbor distances, relying on R-Trees for speed - Steinhardt's BOOPs in 2d - Gyromorphic correlation in 2d - Voronoi quantities (nearest neighbor distance, Voronoi cell area, Voronoi number of neighbors) and option to compute quantities averaged over Voronoi neighbors in 2d - Cluster tagging according to metric distance between particles - Neighbor counts using metric cut-off, including for polydisperse systems

TODO

  • Carry over Steinhardt's 3d BOOPs from hyperalg
  • Compute a few quantities from R-Tree
  • Add simple K-function and/or Fry plots functions?
  • Add an option to normalize g via the summands, g(r) = sum (bin / norm(bin)) instead of g(r) = sum(bin) / norm(r).
  • Try to implement a kernel-based version of g to reduce binning issues?
  • Think of other useful functions?
  • Clean up front-end
  • Refactor lib.rs with separate files and classes; possibly make a few functions there a bit more type-agnostic (par_iter permitting).

Owner

  • Name: Martiniani Lab
  • Login: martiniani-lab
  • Kind: organization
  • Location: Minneapolis, MN

Citation (citation.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Casiulis"
  given-names: "Mathias"
  orcid: "https://orcid.org/0000-0002-5370-076X"
title: "rusted_core"
date-released: 2024-03-10
url: "https://github.com/martiniani-lab/rusted_core"

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Dependencies

Cargo.toml cargo
pyproject.toml pypi